Abstract:
As the fiber-reinforced polymer matrix composites give good strength and can
work in rigorous environmental conditions, nowadays, more focus is given to
study the behavior of these materials under different operating conditions. Due
to the environmental concern, the focus on the natural fiber reinforced polymer
matrix composite is enhancing both in research and industrial sectors. Currently,
the focus has been given to unifying solid fillers with the polymer matrix
composite to improve their mechanical and tribo properties. Aligned to this, the
present work discusses the effect of various weight fractions of fillers (Flyash,
SiC, and graphite) on the frictional behavior of natural fiber (cotton) polyester
matrix composites. The specimen prepared with a hand lay-up process followed
by compression molding. A plan of experiments, response surface technique,
was used to obtain a response in an organized way by varying load, speed, and
sliding distance. The test results reveal that different weight concentration of
fillers has a considerable result on the output. The frictional behavior of
materials evaluated by general regression and artificial neural network. The
validation experiment effects show the estimated friction by using the artificial
neural network was closer to experimental values compare to the regression
models.
